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https://www.selleckchem.com/products/tdi-011536.html Electrocatalytic performance of low-cost graphitic carbon nitride (CN) is greatly limited by its limited conductivity and small specific surface area. Herein, a simple and cost-effective idea to produce novel nanocomposite is constructed by the CN and cetyl trimethyl ammonium bromide functionalized carbon black (CB) anchored platinum nanoparticles as highly efficient oxygen reduction catalysts based on gamma irradiation. The assembled carbon nitride/positive carbon black anchoring PtNPs (Pt/CN2-CB+1) catalyst exhibits significantly improved specific surface area, high graphitization, and uniformly dispersed ultra-small platinum nanoparticles. For the oxygen reduction reaction (ORR) performance, the catalyst shows more positive onset-potential (0.93 V versus RHE) and larger diffusion limiting current density (5.65 mA cm-2) compared with benchmark Pt/C catalysts in alkaline medium. Moreover, the Pt/CN2-CB+1catalyst exhibits a small Tafel slope (92 mV dec-1). Besides, the catalyst was demonstrated the remarkable methanol tolerance and good long-term stability under working conditions. This work provides a new and effectiveγ-rays irradiation for synthesizing the carbon nitride catalysts for energy conversion and storage applications.Objective.In the last decade, the advent of code-modulated brain-computer interfaces (BCIs) has allowed the implementation of systems with high information transfer rates (ITRs) and increased the possible practicality of such interfaces. In this paper, we evaluate the effect of different numbers of targets in the stimulus display, modulation sequences generators, and signal processing algorithms on the accuracy and ITR of code-modulated BCIs.Approach.We use both real and simulated electroencephalographic (EEG) data, to evaluate these parameters and methods. Then, we compared numerous different setups to assess their performance and identify the best configurations. We also evaluated the de

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